14. Related Codes (*)

Here we summarize some codes used in stellar dynamics that are similar to NEMO. We only list codes that are (publically) available. SPH/hydro codes are currently not included. See also ASCL to find more codes.

First we start off with some expanded examples on a few specific codes that have a tighter connection to NEMO:

14.1. AMUSE

AMUSE (Astrophysical Multipurpose Software Environment) originates some ideas from its predecessors: ACS, StarLab and NEMO, but uses the python language. Another feature of AMUSE is that python is also the glue shell between legacy codes that can orchestrate simulations taking components from different codes, whereas in NEMO legacy codes have a NEMO CLI interface, at best.

For seasoned AMUSE users, here we highlight some differences between the two, and give some examples how to achieve the same task in NEMO and AMUSE.

14.1.1. Differences

• Shell: NEMO uses a Unix shell, AMUSE uses python (ipython, jupyter, …).

• Community Code: Both packages maintain a tight connection to legacy software and community codes. You can find them in $AMUSE/src/amuse/community and $NEMO/usr resp.

• Units: NEMO uses dimensionless values, and units are implied. Most programs actually use virial units where G=1, but there are a few programs (e.g. galaxy, nbodyX) that use other units. The units(1NEMO) tries to help you converting. AMUSE (optionally?) attaches units to numbers , using a python trick, e.g.

from amuse.units import units

mass   = 1.0 | units.MSun

astropy users might be a bit baffled, since this looks very different. But

m1 = mass.as_astropy_quantity()

will look more familiar. In pure astropy it might look as follows:

from astropy import units as u

m = 1.0 * u.solMass
m2 = m.to(u.kg).value

14.1.2. Examples: Creating a Plummer sphere

Here we create a Plummer sphere, in virial units, in NEMO, and display an X-VX projection on the sky in a shell session:

source /opt/nemo/nemo_start.sh

mkplummer p100 100
snapplot p100 xvar=x yvar=vx

or in the style of using pipes this can be a one liner

mkplummer - 100 | snapplot - xvar=x yvar=vx

And in AMUSE the following python session can do something similar:

Todo

figure out the right py-gnuplot

from amuse.units import units
from amuse.units import nbody_system
from amuse.ic.plummer import new_plummer_sphere

convert_nbody = nbody_system.nbody_to_si(100.0 | units.MSun, 1 | units.parsec)
plummer = new_plummer_sphere(1000, convert_nbody)


plotter = Gnuplot.Gnuplot()
plotter.splot(plummer.position.value_in(units.parsec))

The AMUSE manual has some NEMO I/O examples.

14.1.3. Installation

For the benefit of NEMO users, AMUSE can usually be installed easily as follows:

pip install amuse

but this can take a while as it finds the right dependencies and needs to compile massive amounts of code. Some of these can easily fail if you don’t have the correct prerequisites (e.g. MPI).

A potentially faster way is to first install the AMUSE frame work and then the selected module(s):

pip install amuse-framework
pip install amuse-seba amuse-brutus

There are many more details in the AMUSE installation manual.

14.2. Martini

There is an expanded example in https://teuben.github.io/nemo/examples/eagle.html, and some supporting notes are in $NEMO/usr/martini.

It can also be installed with

pip install astromartini

14.3. ClusterTools (*)

This python package can also read NEMO (gyrfalcON) files. More on this later.

14.4. ZENO

ZENO is Josh Barnes’ version of an earlier version of NEMO that he continues to develop. We also keep a zeno manual page highlighting some differences.

Warning

Adding ZENO to NEMO will result in some programs that have duplicated names.

14.4.1. Installation

For the benefit of NEMO users, ZENO can usually be installed as follows:

cd $NEMO/usr/zeno
make zeno

This will currently download two repos: zeno_jeb and zeno_pjt. Pick one by using a symlink to become the official one for the install:

ln -s zeno_pjt zeno
source zeno_start.sh
cd zeno
make -f Zeno

Now various ZENO commands are available:

ls $ZENOPATH/bin

14.5. STARLAB

14.5.1. Installation

For the benefit of NEMO users, STARLAB can usually be installed as follows:

mknemo starlab

14.5.2. Examples

These examples were taken from http://www.sns.ias.edu/~starlab/examples/, but an up-to-date list may be found in the file EXAMPLES in the Starlab distribution. If installed within NEMO, this should be in $NEMO/local/starlab/EXAMPLES.

For details on a specific tool, type

tool-name --help

• Create a linked list of 100 equal-mass nodes of unit total mass

makenode -n 100 -m 1

• Create a system of 100 nodes with a Salpeter mass spectrum with masses

in the range 0.5 to 10

makenode -n 100 | makemass -f 1 -x -2.35 -l 0.5 -u 10

• Create a system of 100 nodes with a mass spectrum and evolve the stars

without dynamics

makenode -n 100 | makemass -f 1 -x -2.35 -l 0.5 -u 10 \
                | ...(to come)...

• Create a 500-particle Plummer model, with numbered stars, scaled to

standard dynamical units

makeplummer -n 500 -i

• Create a 500-particle W0 = 5 King model, with numbered stars, unscaled

makeking -n 500 -w 5 -i -u

• Create a 500-particle W0 = 5 King model with a Miller-Scalo mass

spectrum between 0.1 and 20 solar masses, then rescale to unit total mass, total energy -0.25, and virial ratio 0.5 and display the results graphically

makeking -n 500 -w 5 -i -u \
| makemass -F Miller_Scalo -l 0.1 -u 20 \
| scale -m 1 -e -0.25 -q 0.5 \
| xstarplot -l 5 -P .5

• Create a 500-particle W0 = 5 King model with a Miller-Scalo mass

spectrum between 0.1 and 20 solar masses, add in a 10 percent 1-10 kT binary population, then rescale to unit total mass, total energy (top-level nodes) -0.25, and virial ratio (top-level nodes) 0.5, and finally verify the results by analyzing the final snapshot

makeking -n 500 -w 5 -i -u \
| makemass -f 2 -l 0.1 -u 20 \
| makesecondary -f 0.1 -l 0.25 \
| scale -m 1 -e -0.25 -q 0.5 \
| makebinary -l 1 -u 10 \
| sys_stats -n

• Evolve this model without stellar evolution for 100 dynamical times,

with log output every dynamical time and snapshot output every 10 dynamical times, with a self-consistent tidal field, removing escapers when they are more than two Jacobi radii from the cluster center

makeking -n 500 -w 5 -i -u \
| makemass -f 2 -l 0.1 -u 20 \
| makesecondary -f 0.1 -l 0.25 \
| makebinary -l 1 -u 10 \
| scale -m 1 -e -0.25 -q 0.5 \
| kira -t 100 -d 1 -D 10 -Q -G 2

• Create a King model with a power-law mass spectrum and a binary

population, then evolve it with stellar and binary evolution

makeking -n 500 -w 5 -i -u \
| makemass -f 1 -x -2.0 -l 0.1 -u 20 \
| makesecondary -f 0.1 -l 0.1 \
| add_star -Q 0.5 -R 5 \
| scale -M 1 -E -0.25 -Q 0.5 \
| makebinary -f 1 -l 1 -u 1000 -o 2 \
| kira -t 100 -d 1 -D 10 -f 0.3 \
                  -n 10 -q 0.5 -Q -G 2 -B

• Perform a series of 100 3-body scattering experiments involving an

equal-mass circular binary and a double-mass incomer, with impact parameter equal to the binary semimajor axis, relative velocity at infinity half that needed for zero total energy, and all other parameters chosen randomly, and display the results as a movie

scatter3 -m 0.5 -e 0 -M 1 -r 1 -v 0.5 \
         -n 100 -C 5 -D 0.1 \
| xstarplot -l 4

• Compute cross-sections for interactions between a circular binary with

component masses 0.75 and 0.25 and an incoming star of mass 1 and velocity at infinity 0.1, all stars having radius 0.05 binary semimajor axes

sigma3 -d 100 -m 0.25 -e 0 -M 1 -v 0.1 \
       -x 0.05 -y 0.05 -z 0.05

• Create a scattering configuration involving a head-on collision

between a circular binary and a stable hierarchical triple, and verify the result

makescat -M 1.5 -r 0 -v 1 -t -a 1 -e 0 \
         -p -a 1 -e 0 -p1 -a 0.1 -e 0 \
| flatten | make_tree -D 1 | pretty_print_tree

• Create a scattering configuration involving a head-on collision

between a circular binary and a stable hierarchical triple, and integrate it forward in time

scatter -i "-M 1.5 -r 0 -v 1 -t -a 1 -e 0 \
        -p -a 1 -e 0 -p1 -a 0.1 -e 0" \
        -t 100 -d 1 -v

14.6. Yt

yt is a community-developed analysis and visualization toolkit for volumetric data, and handles SnapShot type data.

Warning

using yt will require python3.

More to come. There is a notebook in prep.

14.7. List of Related Codes

Todo

this list needs to be annotated and spiced up with links.

ACS

The Art of Computational Science - How to build a computational lab. In C++ and ruby. With ideas from NEMO and StarLab. | http://www.artcompsci.org/

agama

Action-based galaxy modeling framework. Also usable via $NEMO/usr/agama. | http://ascl.net/1805.008

AMIGA

Adaptive Mesh Investigations of Galaxy Assembly. | http://ascl.net/1007.006

AMUSE

Astrophysical Multipurpose Software Environment. Also usable via $NEMO/usr/amuse. | http://ascl.net/1107.007

arepo

Cosmological magnetohydrodynamical moving-mesh simulation code. | http://ascl.net/1909.010

bhint

High-precision integrator for stellar systems | https://ascl.net/1206.005

bonsai

N-body GPU tree-code, in AMUSE. | http://ascl.net/1212.001

brutus

See also AMUSE

Catena

Ensemble of stars orbit integration | https://ascl.net/1206.008

CGS

Collisionless Galactic Simulator. Also usable via NEMO with the runCGS interface. | http://ascl.net/1904.003

ChaNGa

Charm N-body GrAvity solver | http://ascl.net/1105.005

clustertools

A Python package with tools for analysing star clusters. | https://github.com/webbjj/clustertools

DICE

Disk Initial Conditions Environment | https://ascl.net/1607.002

Fewbody

Numerical toolkit for simulating small-N gravitational dynamics | http://ascl.net/1208.011

fractal

A parallel high resolution Poisson solver for an arbitrary distribution of particles. | https://github.com/jensvvillumsen/Fractal

gadgetX

A Code for Cosmological Simulations of Structure Formation. Several versions available, X=1,2,3,4. gadget2 also available via $NEMO/usr/gadget. | http://ascl.net/0003.001

Gala

Galactic astronomy and gravitational dynamics. | http://ascl.net/1302.011

galaxy

N-body simulation software for isolated, collisionless stellar systems. The older version still usable via NEMO with the rungalaxy interface. | http://ascl.net/1904.002

galpy

Galactic dynamics package (python) | http://ascl.net/1411.008

GalPot

Galaxy potential code | http://ascl.net/1611.006

GANDALF

Graphical Astrophysics code for N-body Dynamics And Lagrangian Fluids | http://ascl.net/1602.015

GENGA

Gravitational ENcounters with Gpu Acceleration | http://ascl.net/1812.014

Glnemo2

Interactive Visualization 3D Program | http://ascl.net/1110.008

GraviDy

Gravitational Dynamics. Also usable via NEMO with the rungravidy interface. | http://ascl.net/1902.004

gsf

galactic structure finder | http://ascl.net/1806.008

gyrfalcON

Dehnen’s code. Included in NEMO | http://ascl.net/1402.031

hermite

In AMUSE.

HiGPUs

Hermite’s N-body integrator running on Graphic Processing Units. Part of AMUSE. | https://ascl.net/1207.002

HUAYNO

Hierarchically split-Up AstrophYsical N-body sOlver N-body code. Part of AMUSE. | http://ascl.net/2102.019

Hydra

A Parallel Adaptive Grid Code | http://ascl.net/1103.010

hnbody

also | http://ascl.net/1201.010

ICICLE

Initial Conditions for Isolated CoLlisionless systems https://ascl.net/1703.012 | http://ascl.net/1703.012

identikit

1: A Modeling Tool for Interacting Disk Galaxies. | https://ascl.net/1011.001 2: An Algorithm for Reconstructing Galactic Collisions. | https://ascl.net/1102.011

InitialConditions

Website with a collection of programs for integrating the equations of motion for N objects, implemented in many languages, from Ada to Swift. | http://www.initialconditions.org/codes

JSPAM

Interacting galaxies modeller | http://ascl.net/1511.002

limepy

Lowered Isothermal Model Explorer in PYthon. | https://ascl.net/1710.023

MARTINI

Mock spatially resolved spectral line observations of simulated galaxies Also usable via $NEMO/usr/martini, see example. | http://ascl.net/1911.005

mcluster

Make a plummer. Also usable via NEMO | http://ascl.net/1107.015

McScatter

Three-Body Scattering with Stellar Evolution | http://ascl.net/1201.001

mercury

A software package for orbital dynamics. In AMUSE. | http://ascl.net/1209.010

MYRIAD

N-body code for simulations of star clusters | https://ascl.net/1203.009

nbodyX

Where X=0,1,2,3,4,5,6,6++,7 Also usable via NEMO with the runbodyX interface. | http://ascl.net/1904.027

nbody6tt

Tidal tensors in N-body simulations | http://ascl.net/1502.010

nbodykit

Massively parallel, large-scale structure toolkit | http://ascl.net/1904.027

nbody6xx

Alias for nbody6++ Also usable via NEMO | http://ascl.net/1502.010

N-BodyShop

Simulation codes of astrophysical phenomenon with particle methods. (tipsy, changa, gasoline) | https://github.com/N-BodyShop

nemesis

Another code to document. | http://ascl.net/1010.004

NEMO

Stellar Dynamics Toolbox. Our current version is 4. | http://ascl.net/1010.051

NIGO

Numerical Integrator of Galactic Orbits | https://ascl.net/1501.002

N-MODY

A code for Collisionless N-body Simulations in Modified Newtonian Dynamics | http://ascl.net/1102.001

octgrav

in AMUSE. | http://ascl.net/1010.048

partiview

Immersive 4D Interactive Visualization of Large-Scale Simulations | https://ascl.net/1010.073

PENTACLE

Large-scale particle simulations code for planet formation | http://ascl.net/1811.019

petar

Another code to document. | http://ascl.net/2007.005

plumix

another | http://ascl.net/1206.007

pNbody

A python parallelized N-body reduction toolbox https://ascl.net/1302.004

pycola

N-body COLA method code | http://ascl.net/1509.007

pyfalcon

Python interface for gyrfalcON | https://github.com/GalacticDynamics-Oxford/pyfalcon

pynbody

N-Body/SPH analysis for python. | http://ascl.net/1305.002

QYMSYM

A GPU-accelerated hybrid symplectic integrator | https://ascl.net/1210.028

RAMSES

A new N-body and hydrodynamical code | https://ascl.net/1011.007

Raga

Monte Carlo simulations of gravitational dynamics of non-spherical stellar systems | http://ascl.net/1411.010

rebound

Multi-purpose N-body code for collisional dynamics | https://ascl.net/1110.016 Also usable via NEMO

SecularMultiple

Hierarchical multiple system secular evolution model | http://ascl.net/1909.003

sidm-nbody

Monte Carlo N-body Simulation for Self-Interacting Dark Matter | http://ascl.net/1703.007

slimplectic

Discrete non-conservative numerical integrator | http://ascl.net/1507.005

smalln

in AMUSE. | http://ascl.net/1106.012

smile

orbits? | http://ascl.net/1308.001

SpaceHub

High precision few-body and large scale N-body simulations | http://ascl.net/2104.025

SpheCow

Galaxy and dark matter halo dynamical properties | http://ascl.net/2105.007

Starlab

Also usable via NEMO | https://ascl.net/1010.076

Swarm-NG

Parallel n-body Integrations | https://ascl.net/1208.012

Torch

Coupled gas and N-body dynamics simulator | http://ascl.net/2003.014

TPI

Test Particle Integrator | http://ascl.net/1909.004

UNSIO

Universal Nbody Snapshot I/O - See examples.

VINE

A numerical code for simulating astrophysical systems using particles | http://ascl.net/1010.058

yt

A Multi-Code Analysis Toolkit for Astrophysical Simulation Data | https://ascl.net/1011.022

ZENO

Barnes version that was derived from NEMO V1. | https://ascl.net/1102.027 Also usable via NEMO , but watch out for duplicate names of programs

A large number of these codes can also be found by searching on ASCL, for example: https://ascl.net/code/search/dynamics and https://ascl.net/code/search/hermite and https://ascl.net/code/search/orbit and https://ascl.net/code/search/nbody. The last time this list was cross-checked was … 16-jul-2021.

14.8. Python

Python support in NEMO itself is still rudimentary, though the common

cd $NEMO
pip3 install -e .

will add the nemopy module to your python environment. Currently only a simple getparam interface is available.

There are good import and export routines to other N-body formats, through which other toolkits can provide interesting ways to analyze NEMO data. We list a few

• yt toolkit: https://yt-project.org/

• nobodykit: https://nbodykit.readthedocs.io/

• clustep, galstep: https://github.com/elvismello create initial conditions in gadget2 format. ($NEMO/usr/mello)

• galanyl: https://bitbucket.org/ngoldbaum/galaxy_analysis pip install galanyl

• galpy: https://github.com/jobovy/galpy

• unsio: pip install python-unsio python-unsiotools ($NEMO/usr/jcl)

• gala: https://github.com/adrn/gala

• agama: https://github.com/GalacticDynamics-Oxford/Agama - pip install agama ($NEMO/usr/agama)

• pynbody: https://github.com/pynbody/pynbody

• martini: https://github.com/kyleaoman/martini ($NEMO/usr/martini)

• galpak: http://galpak3d.univ-lyon1.fr/index.html - pip install galpak

• amuse: https://github.com/amusecode - pip install amuse-framework

• pygad: https://bitbucket.org/broett/pygad

• SnapGadget: https://github.com/regmachado/SnapGadget

14.9. Categories

Such a niche list of codes made me wonder what kind of meta-data we could use to categorize such dynamics codes, but then perhaps along the lines of the Unified Astronomy Thesaurus project.

dynamics - nbody, orbit, integrator, sph, hydro, analysis, integrator